Humans, not artificial intelligence threats, are the cause of the large majority of cyber-attacks — for now.

More than 85% of incurred cyber losses in the first half of 2026 were from attacks that exploited human error, specifically where the point of failure included phishing, social engineering, or transfer fraud, according to a report out on Thursday from cyber insurer Resilience.

That’s not to say AI is a passive force in cyber-attacks. The report suggests that AI has become a force multiplier in attacks.

For companies exploring alternative risk financing options, captive insurance structures have moved from a niche strategy reserved for the largest corporations to an increasingly accessible tool for a broader range of businesses. Yet despite growing interest, misconceptions about captives persist — and those misunderstandings can lead companies to make decisions that don't align with their long-term goals.

Captives are structured, disciplined vehicles that reward companies with the right mindset, culture, and financial capacity to commit for the long haul.

It’s no surprise given the penetration of artificial intelligence into lives and businesses that it appears insurers are gearing up to exclude AI risk in some of their commercial liability policies.

Three ISO exclusions have garnered more interest from carriers, according to an attorney who practices in the cyber space and an expert who helped write the exclusions.

Insurers may be in a race to adopt and scale artificial intelligence faster than their competitors do, but Norm Hudson, CEO of Staff Boom, cautions that jumping the gun could lead to disaster.

Hudson told InsuranceNewsNet that AI pilots launched without a vision of how to handle different scenarios, prerequisite basics like a standard operating procedure and adequate testing are destined to fail.

The National Oceanic and Atmospheric Administration (NOAA) officially declared El Niño in June 2026 and projects it will strengthen into the 2026-2027 winter, with a peak expected between November and January. NOAA's Climate Prediction Center places the probability of an extreme El Niño event at greater than 60%, based on multiple statistical and physical models. Sea-surface temperatures in the tropical Eastern Pacific showed anomalous warmth as of June 2026, confirmed by NOAA satellite imagery.

Catastrophe modeler Karen Clark & Company (KCC) published a July 2026 white paper analyzing the event's impacts on global weather patterns and loss potential. El Niño is associated with reduced North Atlantic hurricane activity and an active typhoon season in the Northwest Pacific. It is also linked to flooding in California, East Africa, and Peru, along with drought in Australia and Indonesia, the report noted.

The greenhouse gas emissions of Amazon.com Inc. and Alphabet Inc.’s Google spiked in 2025, pointing to a growing problem for the hyperscalers: reconciling their climate goals with the massive amount of energy required to power AI, much of it still generated from fossil fuels.

Amazon’s emissions rose 16% from 2024, the company said in a sustainability report released Wednesday. It emitted about 81 million metric tons of carbon dioxide equivalent last year, roughly as much as the emissions from 19 million gas-powered cars on the road. The increase was driven by data center construction and fuel used for deliveries, the report said.

As businesses across the economy adopt artificial intelligence tools, they face heightened risks and exposures associated with the powerful technology.

One growing concern is professional liability in fields such as law and medicine, where practitioners increasingly rely on AI to enhance efficiency and performance.

Many professionals may be creating “a real exposure for errors and omissions” if they are using AI to create efficiencies without properly vetting the output to ensure it is without hallucinations or information gaps, said Maria Long, New York-based chief underwriting officer at cyber insurer Resilience.

After several years of experimentation with generative AI and machine learning, many carriers have moved beyond asking whether AI has a role in insurance. Instead, they’re grappling with a different question: How do organizations know when an AI pilot is ready to scale?

Industry leaders say the answer has less to do with technological sophistication and more to do with organizational readiness.